AutoML Tool

Train machine learning models automatically without writing a single line of code. Upload your dataset, select a target column, and let our tool do the rest.

AutoML Tool

Upload your dataset, select a target column, and train a machine learning model automatically

Click to upload or drag and drop

Max File Size 100MB

CSV
JSON
Excel (XLSX)
Excel (XLS)

Key Features

No-Code Machine Learning

Everything you need to train, evaluate, and understand machine learning models without coding experience.

  • Classification & Regression

    Automatic Detection

    Our AI automatically detects whether your task is classification or regression based on your data.

  • Automatic Evaluation

    Performance Metrics

    Get key performance metrics like accuracy for classification or R² for regression tasks.

  • Real-time Processing

    Instant Results

    Receive instant updates on your model's training progress and insights.

  • One-Click Training

    Simple Setup

    Just upload your CSV, Excel, or JSON file, select your target column, and click train.

Frequently Asked Questions

Learn how our AutoML Tool works and get answers to common questions.

What is AutoML and how does it work?
AutoML (Automated Machine Learning) automatically handles the process of building and evaluating machine learning models. Our tool analyzes your dataset, determines whether you need classification or regression, preprocesses the data, and trains a model without requiring you to write any code.
What file formats does the AutoML tool support?
Our AutoML tool supports CSV, Excel (.xlsx, .xls), and JSON file formats. The maximum file size allowed is 100MB to ensure quick processing.
What's the difference between classification and regression?
Classification is used when predicting categories or classes (like 'yes/no' or 'fraud/not fraud'), while regression is for predicting continuous numerical values (like prices, temperatures, or ages). Our tool automatically detects which type of model is appropriate for your data.
How do I interpret the model performance metrics?
For classification tasks, we report accuracy (percentage of correct predictions). For regression tasks, we report the R² score, which indicates how well the model explains the variance in the data. Values closer to 1.0 indicate better performance in both cases.
How is my data processed and is it secure?
All data processing happens in-memory and is not stored after your session ends. We use industry-standard machine learning libraries (scikit-learn) to process your data, and only you have access to the results.

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